Token导航 LogoToken导航TokenDH.com
研究检索external-servicegithub未标认证来源可访问许可证需确认审计通过

orchestrationorchestration 搜索

Agent Skill

orchestration 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

766

周安装

31

GitHub Stars

10

下载量

241
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:orchestration(orchestration 搜索)
来源仓库:https://github.com/oakoss/agent-skills
仓库路径:skills/orchestration
安装命令:
npx skills add https://github.com/oakoss/agent-skills --skill orchestration
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/oakoss/agent-skills --skill orchestration

简介

orchestration 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。

  • 可结合来源仓库、安装命令和原始 README 继续核验具体用法。
  • 安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。
  • 适用于研究检索类 Agent 工作流,尤其关注工作流编排与调度场景。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

Orchestration

Overview

Coordinates skills, frameworks, and workflows across the project lifecycle. Combines pattern-based project classification with goal decomposition, hierarchical task planning, and multi-agent coordination.

Use this skill for project-level workflow decisions: which frameworks to activate, in what order, and how to validate progress between phases. For Claude Code-specific agent implementation details (agent configuration, batch sizing, prompt engineering), use the agent-patterns skill instead.

This skill does NOT replace project management tools. It provides the decision framework for sequencing capabilities and validating readiness at each transition point.

Quick Reference

NeedAction
Identify project typeClassify as Pattern A / B / C
Sequence frameworksFollow pattern-specific phase order
Decompose a goalExtract required effects, match capabilities
Validate readinessCheck phase-gate criteria before advancing
Find alternativesGenerate fallback capabilities per step
Score a planEvaluate cost, latency, risk, diversity
Coordinate agentsSelect orchestration pattern for task type
Pass contextUse context distillation for subagents

Pattern Identification

Classify every project before selecting frameworks or skills.

PatternCharacteristicsTimeline
A: Simple FeatureExisting system, well-understood, single-team1-5 days
B: New Product/SystemFrom scratch, security/compliance matters4-12 weeks
C: AI-Native/ComplexAI agents, RAG, knowledge graphs, orchestration8-20 weeks

Phase Gates

Do not advance without meeting gate criteria.

GateEntry Criteria
Design (Phase 2)PRP complete, problem validated, success metrics, user stories
Development (3)Architecture documented, data model designed, security threats mapped
Testing (Phase 4)Features complete, unit tests over 80%, code review, SAST clean
Deployment (5)All tests passing, UAT completed, security tested, coverage over 90%

Scoring Function

Plans are evaluated using weighted utility:

FactorWeightScores
Cost0.3free=1.0, low=0.8, medium=0.5, high=0.2
Risk0.3safe=1.0, low=0.8, medium=0.5, high=0.2
Latency0.2instant=1.0, fast=0.7, slow=0.3
Diversity0.2min(unique_domains / 5, 1.0)

Modifiers: recently used (within 3 steps) gets -30% penalty; novel capability gets +20% bonus.

Multi-Agent Orchestration Patterns

PatternUse Case
HierarchicalParent delegates to specialized subagents
SequentialChain of experts (architect -> dev -> review)
ParallelIndependent tasks running simultaneously
HandoffOne agent passes context to the next

Key rules: max delegation depth of 3, use context distillation (not full codebase), log all agent interactions.

MCP Integration

MCP (Model Context Protocol) standardizes how agents connect to external tools, data sources, and prompt templates. The orchestrator discovers available MCP servers at startup and routes tool calls from subagents to the correct server.

MCP PrimitiveRole in Orchestration
ResourcesDiscover available data (schemas, configs, docs) before work
ToolsExecute validated actions with typed arguments
PromptsReuse domain-specific instruction templates across agents
SamplingAllow servers to request AI reasoning mid-execution

Common Mistakes

MistakeCorrect Pattern
Treating all projects as Pattern A (simple feature)Classify first: Pattern A (simple), B (new product), C (AI-native) before selecting frameworks
Skipping phase gates to move fasterEnforce gate criteria before advancing; skipping causes compounding rework
Activating all available skills simultaneouslyLimit to 1-3 skills per phase with clear deliverables and handoffs
No decision logging for capability choicesLog rationale, alternatives considered, scores, and rejection reasons at each step
Building HTN plans without validating preconditionsCheck project state (files, dependencies, env vars) against each capability's requirements first
Delegating without a clear objective manifestEvery subagent needs an objective, constraints, max tokens, and available tools
Passing entire codebase to subagentsUse context distillation to pass only relevant symbols and facts

Delegation

  • Discover project pattern and classify scope: Use Explore agent to survey the codebase, dependencies, and requirements
  • Execute multi-phase orchestration plan: Use Task agent to implement phase-specific deliverables with gate validation
  • Design architecture and capability sequences: Use Plan agent to decompose goals and build scored HTN plans

References

  • goal-decomposition.md -- HTN planning, goal analysis, capability matching, precondition validation, scoring, decision logging
  • project-patterns.md -- Pattern A/B/C classification, phase sequences, skill coordination by phase, parallelization
  • multi-agent-coordination.md -- Hierarchical, sequential, parallel orchestration patterns, delegation manifests, recursion limits
  • mcp-orchestration.md -- MCP architecture, resources, tools, prompts, multi-server orchestration, bidirectional sampling
  • context-distillation.md -- Symbol indexing, fact extraction, recursive context reduction, token management
  • error-handling.md -- Objective drift, tool failure, context overflow, circuit breakers, recovery strategies, logging

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

36.16%
按下载量换算87

Claude

29.58%
按下载量换算71

Cursor

20.86%
按下载量换算50

Gemini CLI

9.88%
按下载量换算24

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

external-service

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

继续浏览同类 Skills